Computer animated faces have found their way into a wide variety of areas. Starting from entertainment like computer games, through television and films to user interfaces using “talking heads”. Animated faces are also becoming popular in web applications in form of human-like assistants or newsreaders. This thesis presents a few aspects of dealing with human face animations, namely: editing, playing and transmitting such animations. It describes a standard for handling human face animations, the MPEG-4 Face Animation, and shows the process of designing, implementing and evaluating applications compliant to this standard. First, it presents changes introduced to the existing components of the Visage|toolkit package for dealing with facial animations, offered by the company Visage Technologies AB. It also presents the process of designing and implementing of an application for editing facial animations compliant to the MPEG-4 Face Animation standard. Finally, it discusses several approaches to the problem of streaming facial animations over the Internet or the Local Area Network (LAN).

Previous studies examining memory biases for threatening faces in social anxiety (SA) have yielded inconclusive results. In the present study, memory and expectancy biases were tested within the context of a novel face recognition paradigm that was designed to offset some of the methodological challenges that have hampered previous research. Undergraduates with high (n = 40) and low (n = 40) levels of SA viewed a series of neutral faces randomly paired with phrases that communicated positive or negative social feedback. Participants’ recognition memory was tested for previously encountered faces, and for their categorization of each encoded face as having been associated with negative (mean) or positive (nice) interpersonal statements. For new faces, participants were asked whether the person seemed mean or nice. Results provided no evidence in support of a general memory bias for threatening (mean) faces among high SA individuals, but instead suggested that high SA individuals lack a positive expectancy bias to appraise new social partners as being nice. Implications are considered for cognitive behavioral and interpersonal models of SA.

This in an essay concerning the use of humor in male communication. Primarily, I have focused on studying how jokes can be used as a sanction for the training of members in a (male) group. I have found great inspiration in Goffman’s thoughts on a social face and the use of humor to protect this perceived face. Initially I started to reflect on men’s reluctance to discuss masculinity and their thoughts about the meaning of being a man. Every time I tried to hold a serious conversation, my male friends made a joke out of it. I seemed to meet a tirade of stereotypes and ironic statements. I started to think that maybe men can’t talk about masculinity in groups because of a fear of losing face? Maybe it might be so, that the concept of being a “real man” is so diffuse and loose that men today don’t know what we expect of them? This uncertainty affects men’s social life; there is a need for common ground and security. In order to express an opinion about the act joking as well as the use of humor in male community, I first tried to familiarize myself with the prevailing notions of masculinity. I learned that the group is a powerful resource for promoting the use of stereotypes as well as the use of humor to create a sense of belonging or penalize those who do “wrong”. Jokes of all kind, friendly emphasis as well as more aggressive forms thrive in groups. I also noted that the type of humor is different in single-sex groups compared to humor in mixed gender groups. In addition to discussing the weight of group mentality I also write about body language, the importance of the ambiguity of humor and how humor can sanction in two ways: Laughter from the group: The target is sanctioned Laughter fails: The source gets sanctioned

One of the main diagnostic criteria for Asperger Syndrome is a severe social impairment (American Psychiatric Association [DSM-IV-TR] 2000), something that has often been connected to a more specific impairment in facial recognition. However, the main diagnostic tool (the DSM-IV-TR) has received much criticism during later years and is soon to be revised (Woodbury-Smith & Volkmar 2009). Among other things, many researchers claim that the diagnosis should be complemented with a sliding scale of severity (Ring, Woodbury-Smith, Watson, Wheelright & Baron-Cohen 2008). The use of facial information is central in the social interaction of humans, evident in the special patterns of visual scanning that people employ for facial stimuli (Yarbus 1967). Because of that, this symptom of Asperger Syndrome has become a high research priority. The impairment in facial recognition has been connected to a bias towards detail based processing (McPartland, Webb, Keehn & Dawson 2010). A recent study also connects this to an unusually high visual acuity, which could result in a disposition to focus on small facial features. In the present study. facial stimuli were prepared to provoke memory conjunction errors. This type of memory error means that a person erroneously claims to recognize a face assembled by pieces of previously shown stimuli. If a person is more prone to do so, that would imply that he or she is more focused on details than on configural information (Danielsson 2006). Two groups were tested, one consisting of non-diagnosed adults and one of adults diagnosed with Asperger Syndrome. A test for visual acuity was administered, which was followed by a series of facial recognition tasks. Responses in the latter part were given with a computer mouse, and eye fixations were recorded using a head mounted eye-tracking device. Three hypotheses were formulated. First, persons with AS were expected to perform more poorly in all facial recognition tasks. Second, persons with AS were expected to make more conjunction errors than test group subjects. Finally, persons with AS were expected to display a mean visual acuity significantly higher than that of the test group. However, no significant differences emerged between the groups in relation to either of the hypotheses, and results could not be referred to flaws in the experimental setup. Therefore, these results are taken to display the heterogeneity of the Asperger Syndrome population, and possibly the importance of early training measures to compensate for social impairments.

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With the blooming of economy after the policy of reforming and opening up, China has become the world's factory, and meanwhile, the increasing income level has led to the demand for luxury consumption. However, those who cannot afford luxury consumption in the Chinese market turned to the counterfeit goods to meet their needs for a conspicuous satisfaction. For the counterfeiting issues in Chinese market, Chinese cultural has been blamed for the main cause, but rarely have researchers taken a delicate view of Chinese culture. This study take the concepts of authoritarian personality and face maintenance which are important in the Chinese cultural characteristics, combining with normative beliefs and cognition of regulative failure as independent variables to identify their relations with the attitude toward counterfeit boutique purchasing behavior, the dependent variable in this study. Meanwhile, we discovered some interesting findings after comparing data from Taiwan and China. In this study, cultural dimensions are used in market segmentation of strategic consideration, hoping for discuss the rampant counterfeiting problems in China. This study provides quality brands in the Chinese market different ways of thinking to fight against counterfeiting.

We propose a novel approach for segmentation of human objects, including face and body, in image sequences. In modern video coding techniques, e.g., MPEG-4 and MPEG-7, human objects are usually the main focus for multimedia applications. We combine temporal and spatial information and employ a neuro-fuzzy mechanism to extract human objects. A fuzzy self-clustering technique is used to divide the video frame into a set of segments. The existence of a face within a candidate face region is ensured by searching for possible constellations of eye-mouth triangles and verifying each eye-mouth combination with the predefined template. Then rough foreground and background are formed based on a combination of multiple criteria. Finally, human objects in the base frame and the remaining frames of the video stream are precisely located by a fuzzy neural network which is trained by a SVD-based hybrid learning algorithm. Through experiments, we compare our system with two other approaches, and the results have shown that our system can detect face locations and extract human objects more accurately.

There exist many methods for facial recognition, such as eigenface, templates, artificial neural networks, etc., based on the given facial sample data (patterns). When an input facial image (target) involve simple geometrical transformations and illumination, the performance of these methods are not very satisfactory. In this thesis, following Li et al., we propose a new face recognition system, which can eliminate translation, rotation, scaling, and prospective transformations of facial images automatically, and can also eliminate illumination. According to facial features, we use this method to find the best transformation and the closet illumination, and then to eliminate them for identification by the best matching between a target and the patterns. Finally, we use the least squares method to recognize the target. This method is validated by numerical examples.

3D face modeling is currently a popular area in Computer Graphics and Computer Vision. Many techniques have been introduced for this purpose, such as using one or more cameras, 3D scanners, and many other systems of sophisticated hardware with related software. But the main goal is to find a good balance between visual reality and the cost of the system. In this thesis, reconstruction of a 3D human face from a pair of stereo cameras is studied. Unlike many other systems, facial feature points are obtained automatically from two photographs with the help of a dot pattern projected on the object&amp / #8217 / s face. It is seen that using projection pattern also provided enough feature points to derive 3D face roughly. These points are then used to fit a generic face mesh for a more realistic model. To cover this 3D model, a single texture image is generated from the initial stereo photographs.

Computer interfaces has changed to 3D graphics environments due to its high number of applications ranging from scientific importance to entertainment. To enhance the realism of the 3D models, an established rendering technique, texture mapping, is used. In computer vision, a way to generate this texture is to combine extracted parts of multiple images of real objects and it is the topic studied in this thesis. While the 3D face model is obtained by using 3D scanner, the texture to cover the model is constructed from multiple images. After marking control points on images and also on 3D face model, a texture image to cover the 3D face model is generated. Moreover, effects of the some features of OpenGL, a graphical library, on 3D texture covered face model are studied.